kaira.benchmarks.BenchmarkConfig

Inheritance diagram for BenchmarkConfig

class kaira.benchmarks.BenchmarkConfig(name: str = 'default', description: str = '', seed: int = 42, device: str = 'auto', num_trials: int = 1, timeout_seconds: float | None = None, verbose: bool = True, save_results: bool = True, output_directory: str = './benchmark_results', save_plots: bool = True, save_raw_data: bool = False, batch_size: int = 1000, num_workers: int = 1, memory_limit_mb: float | None = None, snr_range: ~typing.List[float] = <factory>, block_length: int = 1000, code_rate: float = 0.5, model_precision: str = 'float32', compile_model: bool = False, calculate_confidence_intervals: bool = True, confidence_level: float = 0.95, custom_params: ~typing.Dict[str, ~typing.Any] = <factory>)

Bases: object

Configuration for benchmark execution.

Methods

__init__
from_dict	Create config from dictionary.
from_json	Create config from JSON string.
get	Get configuration parameter.
load	Load configuration from file.
save	Save configuration to file.
to_dict	Convert config to dictionary.
to_json	Convert config to JSON string.
update	Update configuration parameters.

Attributes

batch_size
block_length
calculate_confidence_intervals
code_rate
compile_model
confidence_level
description
device
memory_limit_mb
model_precision
name
num_trials
num_workers
output_directory
save_plots
save_raw_data
save_results
seed
timeout_seconds
verbose
snr_range
custom_params

name: str = 'default'

description: str = ''

seed: int = 42

device: str = 'auto'

num_trials: int = 1

timeout_seconds: float | None = None

verbose: bool = True

save_results: bool = True

output_directory: str = './benchmark_results'

save_plots: bool = True

save_raw_data: bool = False

batch_size: int = 1000

num_workers: int = 1

memory_limit_mb: float | None = None

snr_range: List[float]

block_length: int = 1000

code_rate: float = 0.5

model_precision: str = 'float32'

compile_model: bool = False

calculate_confidence_intervals: bool = True

confidence_level: float = 0.95

custom_params: Dict[str, Any]

to_dict() → Dict[str, Any]

Convert config to dictionary.

to_json() → str

Convert config to JSON string.

save(filepath: str | Path) → None

Save configuration to file.

classmethod from_dict(config_dict: Dict[str, Any]) → BenchmarkConfig

Create config from dictionary.

classmethod from_json(json_str: str) → BenchmarkConfig

Create config from JSON string.

classmethod load(filepath: str | Path) → BenchmarkConfig

Load configuration from file.

update(**kwargs) → None

Update configuration parameters.

get(key: str, default: Any = None) → Any

Get configuration parameter.

__init__(name: str = 'default', description: str = '', seed: int = 42, device: str = 'auto', num_trials: int = 1, timeout_seconds: float | None = None, verbose: bool = True, save_results: bool = True, output_directory: str = './benchmark_results', save_plots: bool = True, save_raw_data: bool = False, batch_size: int = 1000, num_workers: int = 1, memory_limit_mb: float | None = None, snr_range: ~typing.List[float] = <factory>, block_length: int = 1000, code_rate: float = 0.5, model_precision: str = 'float32', compile_model: bool = False, calculate_confidence_intervals: bool = True, confidence_level: float = 0.95, custom_params: ~typing.Dict[str, ~typing.Any] = <factory>) → None